Oreilly Answers: A case study of poorly designed LLM powered RAG system

I enjoy reading books on Oreilly learning platform https://learning.oreilly.com/ . For the past month, a new feature on the Oreilly platform called “Answers” has been staring me down, and I haven’t been tempted to click it. Maybe it’s LLM fatigue, or something else I just didn’t give it a try. I do use LLM tools daily but most of these tools I have designed for myself around my workflows.

Today, I decided to give it a try. If you go to a book page like the one I am reading currently https://learning.oreilly.com/library/view/hands-on-large-language/9781098150952/ you will see Answers icon in the right side bar.

When you click on Answers it will show a standard Chat input box and suggestions. We all have seen them million times by now.

It looks like a standard Retrieval Augmented Generation (RAG) use case. When you ask a question it will search in its knowledge base(some sort of Vector/Hybrid search) and then generate the answer.

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